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Technical Reports: CMU-CyLab-09-008

Title:Differential Privacy for Probabilistic Systems
Authors:Michael Carl Tschantz, Anupam Datta, Dilsun Kaynar
Publication Date:May 14, 2009

Abstract

Differential privacy is a promising approach to privacy-preserving data analysis. There is now a well-developed theory of differentially private functions. Despite recent work on implementing database systems that aim to provide differential privacy and distributed systems that use differential privacy as a basis for higher level security properties, there is no formal theory of differential privacy for systems. In this paper, we formulate precise definitions of differential privacy within a formal model of probabilistic systems, relate these definitions to the original definitions, and develop a proof technique based on an unwinding relation for establishing that a given system achieves this privacy definition. We illustrate the proof technique on a representative example motivated by an implemented system.

Full Report: CMU-CyLab-09-008